Effective Strain Image Sequence Selection by Using Semi-Automated Image Processing Technique
| Autor: | Gulam Mahfuz Chowdhury, Md. Taslim Reza, Asif Ahmed, Md. Wahid Tousif Rahman, Md. Mahedi Hasan |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
medicine.diagnostic_test
Pixel Computer science business.industry Effective strain media_common.quotation_subject Visibility (geometry) Pattern recognition Image processing Image sequence medicine Contrast (vision) Elastography Artificial intelligence business Selection (genetic algorithm) media_common |
| Zdroj: | GUB Journal of Science and Engineering. :8-13 |
| ISSN: | 2409-0476 |
| DOI: | 10.3329/gubjse.v7i0.54022 |
| Popis: | One fourth of the cancer detected in women worldwide is breast cancer which leads this as a major threat for women. There are many methods of detecting cancer among which ultra-sound strain imaging is one of the promising techniques. However, in strain sequence, not all the frames show clear tumor visibility. Consequently, in this paper we tested some well-defined algorithms to find only those frames where the tumor is comparatively clearly visible. We have used Mean Pixel Difference (MPD) and Gray- Level Co-occurrence Matrix (GLCM) to find the frames with better tumor visibility. We have tested our methods in several real-life cases and the results have been examined by a professional doctor. The MPD has an accuracy of 96.2% and the GLCM. Contrast has that of 55.55%. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 8-13 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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